Academic journal article The Psychological Record

Empirically Understanding Understanding Can Make Problems Go Away: The Case of the Chinese Room

Academic journal article The Psychological Record

Empirically Understanding Understanding Can Make Problems Go Away: The Case of the Chinese Room

Article excerpt

  You can know the name of a bird in all the languages of the world, but
when you're finished, you'll know absolutely nothing whatever about the
bird ... So let's look at the bird and see what it's doing--that's what
counts. I learned very early the difference between knowing the name of
something and knowing something.
-- Richard Feynman

  The existence of a popular term does create some presumption in favor
of the existence of a corresponding experimentally real concept, but
this does not free us from the necessity of defining the class and of
demonstrating the reality if the term is to be used for scientific
purposes.
-- B. F. Skinner

Does it matter if computers understand? Computers do what they do and do not seem to care what we call it. Still, at least since Linnaeus, and to an even greater extent since Mendeleyev's development of the periodic table, we know the value of classification--not just to order existing knowledge, but more importantly, to serve as a source of new hypotheses (e.g., Emsley, 2001). Furthermore, it seems the phenomenon of understanding must be tackled by anyone wanting to conduct a consistent analysis of problems related to knowledge. Psychologists whose starting point and primary interest has been behavior as such appear to have shared this view (e.g., Kantor, 1926; Parrott, 1984; Skinner, 1957, 1974). The problem of deciding whether certain computer operations should be classified as understanding is important because solving it can help us understand what understanding is.

It is surprising, then, that more often than not, the many authors debating whether computers can understand have failed to make clear what "understanding" means. Instead, discussions have often focused on a certain task, and asked if performing it is a demonstration of understanding. It seems the debate would be more fruitful if things were done in the opposite order. In other words, we should first try to reach agreement concerning what it is we call understanding, and then move on to whether or not an event or a process belongs in that category. As long as clear-cut criteria are lacking, discussions such as the one regarding a computer's possible ability to understand cannot be settled, and seem destined to go on indefinitely. A pivotal contribution to the literature on computer understanding is Searle (1980).

Searle's famous argument is based on the fact that he does not understand Chinese. He asks his readers to suppose that he is locked in a room and given two batches of Chinese writing. With the Chinese script, he is also given a set of rules in English. Searle (1980, p. 418) continues:

    Now suppose also that I am given a third batch of Chinese symbols
    together with some instructions, again in English, that enable me
    to correlate elements of this third batch with the first two
    batches, and these rules instruct me how to give back certain
    Chinese symbols with certain sorts of shapes in response to
    certain sorts of shapes given me in the third batch. Unknown to
    me, the people who are giving me all of these symbols call the
    first batch "a script," they call the second batch a "story,"
    and they call the third batch "questions." Furthermore, they call
    the symbols I give them back in response to the third batch
    "answers to the questions," and the set of rules in English that
    they gave me, they call "the program."

According to Searle, proponents of "strong Al" (Al being artificial intelligence) would claim that by answering questions in Chinese the way he does, Searle in the Chinese Room is demonstrating that he understands the language. Searle himself argues that he obviously does not. Searle's (1980) treatment of understanding in humans and machines has become a classic, rated among the influential works in cognitive science--not, perhaps, because the article is unanimously regarded as a stroke of genius, but because it has generated an almost unparalleled amount of discussion. …

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